Kicking the ball with high power, short reaction time and accuracy are fundamental requirements for any soccer player. Human players acquire these fine low-level sensory motor coordination abilities trough extended training periods that might last for years. In RoboCup the problem has been addressed by engineering design and acceptable, probably sub-optimal, solutions have been found. To our knowledge the automatic development of these abilities has not been yet employed. Certainly no one is willing to damage a robot during an extended, and probably violent, evolutionary learning process in a real environment. In this work we present an approach for the automatic generation (from scratch) of ball-kick behaviors for legged robots. The approach relies on the use of UCHILSIM, a dynamically accurate simulator, and the Back to Reality paradigm to evolutionary robotics, a recently proposed method for narrowing the difference between simulation and reality during robot behavior execution. After eight hours of simulations successful ball-kick behaviors emerged, being directly transferable to the real robot.
